AML (AgreementMakerLight) Eclipse Project
Compound Matching version
Copyright 2013-2014 LASIGE
This product includes software developed at LASIGE by the
SOMER team (http:somer.fc.ul.pt) in collaboration with
the ADVIS Lab (http:www.cs.uic.eduAdvis).
DISCLAIMER:
This software is provided on an "AS IS" BASIS, WITHOUT
WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or
conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY,
or FITNESS FOR A PARTICULAR PURPOSE.
SYSTEM REQUIREMENTS:
AML requires Java SE Runtime Environment 7. It will not
run on older Java versions.
Memory usage depends on the size of the ontologies you are
working with. We recommend a minimum of 2 GB RAM for small
ontologies (<1,000 classes), 4 GB RAM for medium-sized
ontologies (<10,000 classes), 8 GB RAM for large ontologies
(<100,000 classes), and 16 GB RAM for larger ontologies.
Please keep in mind that opening large ontologies may take
several minutes. Likewise, matching large ontologies may
also take several minutes.
COMPOUND AML USAGE:
You can run the Compound AML by opening the CompoundTest
class and inputting your source, target 1 and target
ontologies.
You can use any ontology but we strongly advise to choose
somewhat related ontologies. We also recommend to have a
target 2 ontology with classes with qualifying
characteristics.
ABOUT AML:
AML is a lightweight automated ontology matching system
specialized on biomedical ontologies but applicable to
other domains. It is described in:
- D. Faria, C. Pesquita, E. Santos, I. Cruz, and F. Couto,
AgreementMakerLight Results for OAEI 2013, ISWC Workshop
on Ontology Matching, 2013. - D. Faria, C. Pesquita, E. Santos, M. Palmonari, I. Cruz,
and F. Couto, The AgreementMakerLight ontology matching
system, ODBASE 2013.
The Compound AML is mainly composed of a novel algorithm,
inspired by AML's WordMatcher, which produces compound
matches between three different ontologies. It is also
specialized on biomedical ontologies but it can possibly
be applied to other domains. It is described in:
- Oliveira, D., & Pesquita, C. (2018). Improving the interoperability of biomedical ontologies with compound alignments. Journal of biomedical semantics, 9(1), 1. doi:10.1186/s13326-017-0171-8